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A Bried History of ML

Machine Learning
The term Machine Learning (ML) was first used by Arthur Samuel, one of the pioneers of Artificial Intelligence at IBM, in 1959. The name came from researchers who observed computers recognizing patterns and developed the theory that computers could learn without being programmed to perform specific tasks. They began exploring artificial intelligence to see how capable computers were of learning from data. ML began to pick up speed in 90’s, when it separated from Artificial Intelligence and become its own unique field rooted in statistical modeling and probability theory.

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Improving lapse predictions (sigma 6/2017: LIFE IN-FORCE MANAGEMENT)

Data analytics – descriptive and predictive – can be used to improve retention of inforce business in several ways. Statistical models can be applied to investigate and better understand who lapses and why, using data systematically collected from different sources beyond traditional policyholder information. Based on the understanding of the underlying drivers, predictive models can then provide forecasts of consumer propensity to lapse in response to changes in different variables (eg, price changes). This can be used to appropriately allocate resources to reduce lapses.

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